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Ai Algorithm Engineer Jobs in Virginia (NOW HIRING)

Luck Stone

AI Engineer

Manakin Sabot, VA

$106K - $128K/yr

Ensure the scalability and performance of AI models by optimizing algorithms and utilizing cloud ... TensorFlow Developer Certificate * AWS Certified Machine Learning - Specialty Behavioral ...

Luck Stone Corporation

AI Engineer

VA · On-site

$106K - $128K/yr

Ensure the scalability and performance of AI models by optimizing algorithms and utilizing cloud ... TensorFlow Developer Certificate * AWS Certified Machine Learning - Specialty Behavioral ...

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Ai Algorithm Engineer information

How much do AI automation engineers make?

AI automation engineers typically earn between $80,000 and $150,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in machine learning, deep learning, and programming languages like Python or TensorFlow tend to have higher salaries.

What are some common challenges AI Algorithm Engineers face when deploying models to production environments?

AI Algorithm Engineers often encounter challenges such as ensuring model scalability, maintaining inference speed, and handling the integration of models with existing systems. Additionally, they must address issues like model drift, data pipeline inconsistencies, and the need for continuous monitoring to maintain accuracy over time. Effective collaboration with data engineers, software developers, and DevOps teams is essential for successful deployment and ongoing model performance.

What is the difference between Ai Algorithm Engineer vs Data Scientist?

AspectAi Algorithm EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; knowledge of algorithms and programmingBachelor's or Master's in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDevelops and optimizes AI algorithms, often in R&D or product teamsAnalyzes data, builds models, and provides insights for business decisions
Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, marketing, tech firms

While both roles require strong technical skills and a background in data or algorithms, Ai Algorithm Engineers focus on designing and improving AI algorithms, whereas Data Scientists analyze data to generate insights and build predictive models. The roles often overlap but serve different primary functions within organizations.

What are the key skills and qualifications needed to thrive as an AI Algorithm Engineer, and why are they important?

To thrive as an AI Algorithm Engineer, you need strong expertise in mathematics, programming (especially Python, C++, or Java), and a solid background in computer science or a related field, often supported by a relevant degree. Familiarity with machine learning frameworks (like TensorFlow, PyTorch), data processing tools, and sometimes certifications in AI or data science are typically required. Creative problem-solving, strong analytical thinking, and effective communication are crucial soft skills that set top candidates apart. These skills and qualifications are essential for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technical environments.

What does an AI algorithm engineer do?

An AI algorithm engineer designs, develops, and optimizes algorithms that enable machines to perform tasks such as learning, reasoning, and decision-making. They work with machine learning models, data processing, and programming languages like Python or C++, often using tools like TensorFlow or PyTorch, to create effective AI solutions. Strong analytical skills and knowledge of data structures are essential for this role.

What engineers make $500,000?

Senior AI algorithm engineers with extensive experience, advanced skills in machine learning, deep learning, and data science, and often working in high-demand industries or at leading tech companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at executive or specialized levels.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a highly senior or specialized role such as an AI research director, chief AI officer, or senior machine learning executive, often in large tech companies or financial institutions. These positions usually require extensive experience, advanced skills in machine learning, deep learning, and data science, and may include leadership responsibilities and strategic decision-making.

What are AI Algorithm Engineers?

AI Algorithm Engineers are professionals who design, develop, and optimize algorithms that enable artificial intelligence systems to learn from data and perform complex tasks. They work with machine learning, deep learning, and other AI techniques to create models that can analyze information, make predictions, or automate processes. AI Algorithm Engineers often collaborate with data scientists and software developers to implement and improve AI solutions for various industries, such as healthcare, finance, and technology. Their work involves both theoretical research and practical application, requiring strong programming and mathematical skills.
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Ai Algorithm Engineer jobs near you
Imagery Scientist - EO Middle -Job#781

Imagery Scientist - EO Middle -Job#781

Allen Integrated Solutions

Springfield, VA

Other

Posted 14 days ago

Job description

Imagery Scientist - EO Middle 

Location: Springfield, VA / Washington Metro Area

 TS/SCI REQUIRED/Current CI Poly or Willing to take one Required

Allen Integrated Solutions is supporting NGA's Assurance and Governance Office (QA) Accreditation of AI Models (AGAIM) program. This position will identify and acquire imagery in support of Level 3 Accreditation-the application of the AI algorithm to operational imagery data sets. This position will serve as experts in your respective image modality and prepare imagery of the necessary quality, standards, and requirements. You will develop solutions that are informed by the specific phenomenology limitations and advantages of the sensors and platforms.

 Required Experience/Skills: 

  • Experience with EO imagery analytical products and conducting multi-INT analysis
  • Experience using unstructured, structured, and semi-structured data and visualization tools to exploit data through use of programming and scripting 
  • Experience applying advanced geospatial skills 

Desired 

  • Experience working with or developing machine learning algorithms for exploiting overhead imagery and/or motion imagery

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